Absolute Value Cumulating Based Spectrum Sensing with Laplacian Noise in Cognitive Radio Networks

摘要

Spectrum sensing in the presence of non-Gaussian noise is a challenging problem for cognitive radio networks. However, there are few detectors that can work well in this case. Motivated by these, we propose a spectrum sensing algorithm via absolute value cumulating (AVC) with Laplacian noise. The AVC makes full use of the stochastic properties of Laplacian noise and the central limit theorem. Then the statistic of the proposed detector is derived. A performance analysis about the influence of noise uncertainty in the low signal-to-noise ratio regime is also given, which shows that the SNR Wall of the AVC is half of that of the energy detection. The algorithm are further introduced into existing cooperative spectrum sensing scheme. Simulation results validate the algorithm, and show that the proposed algorithm can improve the performance of existing algorithm at least 3 dB with Laplacian noise.